{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Areal Project"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div>\n",
    "<img src=\"logo.jpg\" width=150 ALIGN=\"left\" border=\"20\">\n",
    "<h1> Starting Kit for raw data (images)</h1>\n",
    "<br>This code was tested with <br>\n",
    "Python 3.6.7 <br>\n",
    "Created by Areal Team <br><br>\n",
    "ALL INFORMATION, SOFTWARE, DOCUMENTATION, AND DATA ARE PROVIDED \"AS-IS\". The CDS, CHALEARN, AND/OR OTHER ORGANIZERS OR CODE AUTHORS DISCLAIM ANY EXPRESSED OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR ANY PARTICULAR PURPOSE, AND THE WARRANTY OF NON-INFRIGEMENT OF ANY THIRD PARTY'S INTELLECTUAL PROPERTY RIGHTS. IN NO EVENT SHALL AUTHORS AND ORGANIZERS BE LIABLE FOR ANY SPECIAL, \n",
    "INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF SOFTWARE, DOCUMENTS, MATERIALS, PUBLICATIONS, OR INFORMATION MADE AVAILABLE FOR THE CHALLENGE. \n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div>\n",
    "    <h2>Introduction </h2>\n",
    "     <br>\n",
    "Aerial imagery has been a primary source of geographic data for quite a long time. With technology progress, aerial imagery became really practical for remote sensing : the science of obtaining information about an object, area or phenomenon.\n",
    "Nowadays, there are many uses of image recognition spanning from robotics/drone vision to autonomous driving vehicules or face detection.\n",
    "<br>\n",
    "In this challenge, we will use pre-processed data, coming from landscape images. The goal is to learn to differentiate common and uncommon landscapes such as a beach, a lake or a meadow.\n",
    "    Data comes from part of the data set (NWPU-RESISC45) originally used in <a href=\"https://arxiv.org/pdf/1703.00121.pdf?fbclid=IwAR16qo-EX_Z05ZpxvWG8F-oBU0SlnY-3BPCWBVVOGPyJcVy7BBqCKjnsvJo\">Remote Sensing Image Scene Classification</a>. This data set contains 45 categories while we only kept 13 out of them.\n",
    "\n",
    "References and credits: \n",
    "Yuliya Tarabalka, Guillaume Charpiat, Nicolas Girard for the data sets presentation.<br>\n",
    "Gong Cheng, Junwei Han, and Xiaoqiang Lu, for the original article on the chosen data set.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Requirements \n",
    "\n",
    "The next cell will install all the required dependencies on your computer. You should consider replacing pip with pip3 if pip is related to python2.7 on your computer, or comment it if you already have the dependencies/are running in the docker of the challenge (runnable with the name areal/codalab:pytorch if you know how to run a docker)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install --user -r requirements.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import random\n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_dir = \"sample_code_submission\"\n",
    "result_dir = 'sample_result_submission/' \n",
    "problem_dir = 'ingestion_program/'  \n",
    "score_dir = 'scoring_program/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sys import path; path.append(model_dir); path.append(problem_dir); path.append(score_dir);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div>\n",
    "    <h1> Step 1: Exploratory data analysis </h1>\n",
    "<p>\n",
    "We provide sample_data with the starting kit, but to prepare your submission, you must fetch the public_data from the challenge website and point to it.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_dir = 'sample_data'\n",
    "data_name = 'Areal'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2 style=\"color:red \" >Warning</h2>\n",
    "\n",
    "<p style=\"font-style:italic\"> In case you want to load the full data </p> \n",
    "Files being big, your computer needs to have enough space available in your RAM. It should take about 3-4GB while loading and 1.5GB in the end."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading sample_data/Areal_train from AutoML format\n",
      "Number of examples = 65\n",
      "Number of features = 49152\n",
      "        Class\n",
      "0       beach\n",
      "1   chaparral\n",
      "2       cloud\n",
      "3      desert\n",
      "4      forest\n",
      "5      island\n",
      "6        lake\n",
      "7      meadow\n",
      "8    mountain\n",
      "9       river\n",
      "10        sea\n",
      "11   snowberg\n",
      "12    wetland\n",
      "Number of classes = 13\n"
     ]
    }
   ],
   "source": [
    "from ingestion_program.data_io import read_as_df\n",
    "data = read_as_df(data_dir  + '/' + data_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <td>meadow</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
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       "<p>5 rows × 49153 columns</p>\n",
       "</div>"
      ],
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       "   pixel_1_1_R  pixel_1_1_G  pixel_1_1_B  pixel_1_2_R  pixel_1_2_G  \\\n",
       "0          145          145          121          113          113   \n",
       "1          193          168          138          191          166   \n",
       "2           83           86           67           65           68   \n",
       "3           16           52           48           15           51   \n",
       "4           60           79           47           80           99   \n",
       "\n",
       "   pixel_1_2_B  pixel_1_3_R  pixel_1_3_G  pixel_1_3_B  pixel_1_4_R    ...     \\\n",
       "0           89           73           75           53           65    ...      \n",
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       "3           47           15           52           45           15    ...      \n",
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       "\n",
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       "2              115              110               91              115   \n",
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       "\n",
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       "0              169              139              202              175   \n",
       "1              172              141              201              176   \n",
       "2              107               88              141              133   \n",
       "3               75               56               68               85   \n",
       "4              135              144              120              137   \n",
       "\n",
       "   pixel_128_128_B    target  \n",
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       "1              145    desert  \n",
       "2              114    meadow  \n",
       "3               66     river  \n",
       "4              147  mountain  \n",
       "\n",
       "[5 rows x 49153 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>count</th>\n",
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       "      <td>65.000000</td>\n",
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       "      <td>65.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>65.000000</td>\n",
       "      <td>65.000000</td>\n",
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       "      <td>102.030769</td>\n",
       "      <td>93.676923</td>\n",
       "      <td>97.230769</td>\n",
       "      <td>102.661538</td>\n",
       "      <td>94.323077</td>\n",
       "      <td>94.353846</td>\n",
       "      <td>99.584615</td>\n",
       "      <td>91.230769</td>\n",
       "      <td>93.076923</td>\n",
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       "      <td>98.015385</td>\n",
       "      <td>99.307692</td>\n",
       "      <td>103.800000</td>\n",
       "      <td>94.523077</td>\n",
       "      <td>97.369231</td>\n",
       "      <td>101.738462</td>\n",
       "      <td>93.076923</td>\n",
       "      <td>95.800000</td>\n",
       "      <td>100.323077</td>\n",
       "      <td>91.600000</td>\n",
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       "      <th>std</th>\n",
       "      <td>63.041794</td>\n",
       "      <td>52.057051</td>\n",
       "      <td>52.828765</td>\n",
       "      <td>64.983356</td>\n",
       "      <td>53.971427</td>\n",
       "      <td>54.017679</td>\n",
       "      <td>63.980815</td>\n",
       "      <td>53.380091</td>\n",
       "      <td>53.738594</td>\n",
       "      <td>64.282168</td>\n",
       "      <td>...</td>\n",
       "      <td>58.560463</td>\n",
       "      <td>63.085241</td>\n",
       "      <td>54.084194</td>\n",
       "      <td>55.020765</td>\n",
       "      <td>60.896575</td>\n",
       "      <td>50.817467</td>\n",
       "      <td>51.335389</td>\n",
       "      <td>55.726509</td>\n",
       "      <td>43.865956</td>\n",
       "      <td>43.464713</td>\n",
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       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>13.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>18.000000</td>\n",
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       "      <th>25%</th>\n",
       "      <td>53.000000</td>\n",
       "      <td>63.000000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>46.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>63.000000</td>\n",
       "      <td>58.000000</td>\n",
       "      <td>53.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>53.000000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>55.000000</td>\n",
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       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>82.000000</td>\n",
       "      <td>88.000000</td>\n",
       "      <td>85.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>96.000000</td>\n",
       "      <td>88.000000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>87.000000</td>\n",
       "      <td>84.000000</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>73.000000</td>\n",
       "      <td>90.000000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>74.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>86.000000</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>96.000000</td>\n",
       "      <td>92.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>141.000000</td>\n",
       "      <td>137.000000</td>\n",
       "      <td>135.000000</td>\n",
       "      <td>139.000000</td>\n",
       "      <td>145.000000</td>\n",
       "      <td>136.000000</td>\n",
       "      <td>136.000000</td>\n",
       "      <td>140.000000</td>\n",
       "      <td>136.000000</td>\n",
       "      <td>136.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>121.000000</td>\n",
       "      <td>152.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>128.000000</td>\n",
       "      <td>138.000000</td>\n",
       "      <td>144.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>135.000000</td>\n",
       "      <td>137.000000</td>\n",
       "      <td>132.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>239.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>245.000000</td>\n",
       "      <td>237.000000</td>\n",
       "      <td>239.000000</td>\n",
       "      <td>242.000000</td>\n",
       "      <td>239.000000</td>\n",
       "      <td>238.000000</td>\n",
       "      <td>243.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>255.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>249.000000</td>\n",
       "      <td>254.000000</td>\n",
       "      <td>235.000000</td>\n",
       "      <td>245.000000</td>\n",
       "      <td>254.000000</td>\n",
       "      <td>232.000000</td>\n",
       "      <td>212.000000</td>\n",
       "      <td>218.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 49152 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       pixel_1_1_R  pixel_1_1_G  pixel_1_1_B  pixel_1_2_R  pixel_1_2_G  \\\n",
       "count    65.000000    65.000000    65.000000    65.000000    65.000000   \n",
       "mean     96.630769   102.030769    93.676923    97.230769   102.661538   \n",
       "std      63.041794    52.057051    52.828765    64.983356    53.971427   \n",
       "min      13.000000    14.000000    14.000000     6.000000    13.000000   \n",
       "25%      53.000000    63.000000    52.000000    44.000000    64.000000   \n",
       "50%      82.000000    88.000000    85.000000    80.000000    96.000000   \n",
       "75%     141.000000   137.000000   135.000000   139.000000   145.000000   \n",
       "max     239.000000   240.000000   245.000000   237.000000   239.000000   \n",
       "\n",
       "       pixel_1_2_B  pixel_1_3_R  pixel_1_3_G  pixel_1_3_B  pixel_1_4_R  \\\n",
       "count    65.000000    65.000000    65.000000    65.000000    65.000000   \n",
       "mean     94.323077    94.353846    99.584615    91.230769    93.076923   \n",
       "std      54.017679    63.980815    53.380091    53.738594    64.282168   \n",
       "min      12.000000     9.000000    13.000000    11.000000    11.000000   \n",
       "25%      49.000000    46.000000    60.000000    48.000000    45.000000   \n",
       "50%      88.000000    74.000000    87.000000    84.000000    77.000000   \n",
       "75%     136.000000   136.000000   140.000000   136.000000   136.000000   \n",
       "max     242.000000   239.000000   238.000000   243.000000   240.000000   \n",
       "\n",
       "            ...         pixel_128_125_B  pixel_128_126_R  pixel_128_126_G  \\\n",
       "count       ...               65.000000        65.000000        65.000000   \n",
       "mean        ...               98.015385        99.307692       103.800000   \n",
       "std         ...               58.560463        63.085241        54.084194   \n",
       "min         ...               12.000000        10.000000        15.000000   \n",
       "25%         ...               60.000000        55.000000        63.000000   \n",
       "50%         ...               90.000000        73.000000        90.000000   \n",
       "75%         ...              121.000000       152.000000       141.000000   \n",
       "max         ...              255.000000       240.000000       249.000000   \n",
       "\n",
       "       pixel_128_126_B  pixel_128_127_R  pixel_128_127_G  pixel_128_127_B  \\\n",
       "count        65.000000        65.000000        65.000000        65.000000   \n",
       "mean         94.523077        97.369231       101.738462        93.076923   \n",
       "std          55.020765        60.896575        50.817467        51.335389   \n",
       "min           9.000000        14.000000        19.000000        14.000000   \n",
       "25%          58.000000        53.000000        60.000000        56.000000   \n",
       "50%          74.000000        74.000000        97.000000        86.000000   \n",
       "75%         128.000000       138.000000       144.000000       130.000000   \n",
       "max         254.000000       235.000000       245.000000       254.000000   \n",
       "\n",
       "       pixel_128_128_R  pixel_128_128_G  pixel_128_128_B  \n",
       "count        65.000000        65.000000        65.000000  \n",
       "mean         95.800000       100.323077        91.600000  \n",
       "std          55.726509        43.865956        43.464713  \n",
       "min          17.000000        22.000000        18.000000  \n",
       "25%          53.000000        64.000000        55.000000  \n",
       "50%          76.000000        96.000000        92.000000  \n",
       "75%         135.000000       137.000000       132.000000  \n",
       "max         232.000000       212.000000       218.000000  \n",
       "\n",
       "[8 rows x 49152 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.image as mpimg\n",
    "%matplotlib inline\n",
    "\n",
    "num_toshow = 6\n",
    "fig, _axs = plt.subplots(nrows=2, ncols=3, figsize=(10,10))\n",
    "fig.subplots_adjust(hspace=0.3)\n",
    "axs = _axs.flatten()\n",
    "\n",
    "for i in range(num_toshow):\n",
    "    img = data.iloc[i].values[:-1].reshape(128,128,3)\n",
    "    label = data.iloc[i].values[-1:]\n",
    "    axs[i].set_title('Example of {}'.format(label))\n",
    "    axs[i].imshow(img.astype(float) / 255)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       target\n",
      "0      desert\n",
      "1      desert\n",
      "2      meadow\n",
      "3       river\n",
      "4    mountain\n",
      "5    snowberg\n",
      "6      meadow\n",
      "7      island\n",
      "8      desert\n",
      "9        lake\n",
      "10     desert\n",
      "11      beach\n",
      "12     forest\n",
      "13   snowberg\n",
      "14     desert\n",
      "15       lake\n",
      "16      cloud\n",
      "17      river\n",
      "18     meadow\n",
      "19        sea\n",
      "20      cloud\n",
      "21      river\n",
      "22     forest\n",
      "23        sea\n",
      "24     island\n",
      "25      beach\n",
      "26    wetland\n",
      "27   snowberg\n",
      "28      beach\n",
      "29      cloud\n",
      "..        ...\n",
      "35   mountain\n",
      "36  chaparral\n",
      "37    wetland\n",
      "38  chaparral\n",
      "39  chaparral\n",
      "40     meadow\n",
      "41       lake\n",
      "42  chaparral\n",
      "43   mountain\n",
      "44        sea\n",
      "45      cloud\n",
      "46    wetland\n",
      "47       lake\n",
      "48  chaparral\n",
      "49   mountain\n",
      "50   snowberg\n",
      "51    wetland\n",
      "52      river\n",
      "53     meadow\n",
      "54   mountain\n",
      "55      beach\n",
      "56      cloud\n",
      "57    wetland\n",
      "58        sea\n",
      "59   snowberg\n",
      "60     island\n",
      "61     island\n",
      "62       lake\n",
      "63      beach\n",
      "64     forest\n",
      "\n",
      "[65 rows x 1 columns]\n"
     ]
    }
   ],
   "source": [
    "print(data.iloc[:, -1:])\n",
    "X = data.iloc[:, :-1]\n",
    "y = data.iloc[:, -1:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 2 : Building a predictive model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2 style=\"color:red \" >Warning</h2>\n",
    "\n",
    "<p style=\"font-style:italic\"> In case you want to load the full data </p> \n",
    "This time, also, still make sure that your RAM has at least 2-3GB available."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Info file found : /home/keanu/Documents/CoursMPI/M2/Projet/Remote-Sensing-Image/starting_kit/sample_data/Areal_public.info\n",
      "========= Reading sample_data/Areal_feat.type\n",
      "[+] Success in  0.00 sec\n",
      "========= Reading sample_data/Areal_train.data\n",
      "[+] Success in  0.83 sec\n",
      "========= Reading sample_data/Areal_train.solution\n",
      "[+] Success in  0.00 sec\n",
      "========= Reading sample_data/Areal_valid.data\n",
      "[+] Success in  0.16 sec\n",
      "========= Reading sample_data/Areal_valid.solution\n",
      "[+] Success in  0.00 sec\n",
      "========= Reading sample_data/Areal_test.data\n",
      "[+] Success in  0.16 sec\n",
      "========= Reading sample_data/Areal_test.solution\n",
      "[+] Success in  0.00 sec\n",
      "DataManager : Areal\n",
      "info:\n",
      "\tusage = Sample dataset Areal data\n",
      "\tname = areal\n",
      "\ttask = multiclass.classification\n",
      "\ttarget_type = Categorical\n",
      "\tfeat_type = Numerical\n",
      "\tmetric = accuracy\n",
      "\ttime_budget = 12000\n",
      "\tfeat_num = 49152\n",
      "\ttarget_num = 13\n",
      "\tlabel_num = 13\n",
      "\ttrain_num = 65\n",
      "\tvalid_num = 13\n",
      "\ttest_num = 13\n",
      "\thas_categorical = 0\n",
      "\thas_missing = 0\n",
      "\tis_sparse = 0\n",
      "\tformat = dense\n",
      "data:\n",
      "\tX_train = array(65, 49152)\n",
      "\tY_train = array(65, 1)\n",
      "\tX_valid = array(13, 49152)\n",
      "\tY_valid = array(13, 1)\n",
      "\tX_test = array(13, 49152)\n",
      "\tY_test = array(13, 1)\n",
      "feat_type:\tarray(0,)\n",
      "feat_idx:\tarray(0,)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from data_manager import DataManager\n",
    "D = DataManager(data_name, data_dir, replace_missing=False, verbose=True)\n",
    "print(D)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = D.data['X_train']\n",
    "Y_train = D.data['Y_train']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Use of the baseline model\n",
    "\n",
    "Using our BasicCNN model needs PyTorch libraries installed.\n",
    "\n",
    "In case you have them but still encounter errors related to them, you should probably do an upgrade : \n",
    "\n",
    "    pip install -U torch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our model is a simple implementation of a Convolutional Neural Network."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from model import BasicCNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "m = BasicCNN(verbose=True)\n",
    "trained_model_name = model_dir + data_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 0 : loss = 2.571903\n",
      "Epoch 1 : loss = 2.554710\n",
      "Epoch 2 : loss = 2.540419\n",
      "Epoch 3 : loss = 2.525594\n",
      "Epoch 4 : loss = 2.509808\n",
      "Epoch 5 : loss = 2.493349\n",
      "Epoch 6 : loss = 2.476958\n",
      "Epoch 7 : loss = 2.461299\n",
      "Epoch 8 : loss = 2.446563\n",
      "Epoch 9 : loss = 2.432736\n"
     ]
    }
   ],
   "source": [
    "m.fit(X_train, Y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y_hat_train = m.predict(D.data['X_train'])\n",
    "Y_hat_valid = m.predict(D.data['X_valid'])\n",
    "Y_hat_test = m.predict(D.data['X_test'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sample_result_submission/Areal_test.predict\r\n",
      "sample_result_submission/Areal_train.predict\r\n",
      "sample_result_submission/Areal_valid.predict\r\n"
     ]
    }
   ],
   "source": [
    "# m.save(trained_model_name)                 \n",
    "result_name = result_dir + data_name\n",
    "from data_io import write\n",
    "write(result_name + '_train.predict', Y_hat_train)\n",
    "write(result_name + '_valid.predict', Y_hat_valid)\n",
    "write(result_name + '_test.predict', Y_hat_test)\n",
    "!ls $result_name*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scoring the result\n",
    "\n",
    "Obviously, since it is made with sample_data, which has too few samples, results won't be really good"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using scoring metric: accuracy\n"
     ]
    }
   ],
   "source": [
    "from libscores import get_metric\n",
    "metric_name, scoring_function = get_metric()\n",
    "print('Using scoring metric:', metric_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ideal score for the accuracy metric = 1.0000\n",
      "Training score for the accuracy metric = 0.4000\n",
      "Valid score for the accuracy metric = 0.3077\n",
      "Test score for the accuracy metric = 0.2308\n"
     ]
    }
   ],
   "source": [
    "print('Ideal score for the', metric_name, 'metric = %5.4f' % scoring_function(Y_train, Y_train))\n",
    "print('Training score for the', metric_name, 'metric = %5.4f' % scoring_function(Y_train, Y_hat_train))\n",
    "if len(D.data['Y_valid']) > 0 and len(D.data['Y_test']) > 0:\n",
    "    print('Valid score for the', metric_name, 'metric = %5.4f' % scoring_function(D.data['Y_valid'], Y_hat_valid))\n",
    "    print('Test score for the', metric_name, 'metric = %5.4f' % scoring_function(D.data['Y_test'], Y_hat_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## confusion matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 0, 0, 0, 0, 2, 1, 0, 0, 1, 1, 0, 0],\n",
       "       [0, 0, 0, 0, 0, 1, 1, 2, 1, 0, 0, 0, 0],\n",
       "       [0, 0, 1, 0, 0, 0, 1, 2, 0, 0, 1, 0, 0],\n",
       "       [0, 0, 0, 0, 0, 0, 0, 4, 1, 0, 0, 0, 0],\n",
       "       [0, 0, 0, 0, 0, 1, 0, 3, 0, 0, 1, 0, 0],\n",
       "       [0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0],\n",
       "       [0, 0, 0, 0, 0, 1, 3, 1, 0, 0, 0, 0, 0],\n",
       "       [0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0],\n",
       "       [0, 0, 0, 0, 0, 0, 0, 2, 3, 0, 0, 0, 0],\n",
       "       [0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 1, 0, 0],\n",
       "       [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0],\n",
       "       [0, 0, 0, 0, 0, 3, 0, 0, 1, 0, 1, 0, 0],\n",
       "       [0, 0, 0, 0, 0, 0, 1, 4, 0, 0, 0, 0, 0]])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "confusion_matrix(Y_train, Y_hat_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## cross validation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "CV scores on sample_data doesn't have enough data, and so isn't meaningful.\n",
    "Run it with the full data to see meaningful values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import make_scorer\n",
    "from sklearn.model_selection import cross_val_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "CV score (95 perc. CI): 0.12 (+/- 0.12)\n"
     ]
    }
   ],
   "source": [
    "scores = cross_val_score(BasicCNN(), X_train, Y_train, cv=3, scoring=make_scorer(scoring_function))\n",
    "print('\\nCV score (95 perc. CI): %0.2f (+/- %0.2f)' % (scores.mean(), scores.std() * 2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Submission"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example\n",
    "\n",
    "Example needs to have python3 installed\n",
    "\n",
    "Test to see whether submission with ingestion program is working"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using input_dir: /home/keanu/Documents/CoursMPI/M2/Projet/Remote-Sensing-Image/starting_kit/sample_data\n",
      "Using output_dir: /home/keanu/Documents/CoursMPI/M2/Projet/Remote-Sensing-Image/starting_kit/sample_result_submission\n",
      "Using program_dir: /home/keanu/Documents/CoursMPI/M2/Projet/Remote-Sensing-Image/starting_kit/ingestion_program\n",
      "Using submission_dir: /home/keanu/Documents/CoursMPI/M2/Projet/Remote-Sensing-Image/starting_kit/sample_code_submission\n",
      "\n",
      "========== Ingestion program version 6 ==========\n",
      "\n",
      "************************************************\n",
      "******** Processing dataset Areal ********\n",
      "************************************************\n",
      "========= Reading and converting data ==========\n",
      "Info file found : /home/keanu/Documents/CoursMPI/M2/Projet/Remote-Sensing-Image/starting_kit/sample_data/Areal_public.info\n",
      "========= Reading /home/keanu/Documents/CoursMPI/M2/Projet/Remote-Sensing-Image/starting_kit/sample_data/Areal_feat.type\n",
      "[+] Success in  0.00 sec\n",
      "========= Reading /home/keanu/Documents/CoursMPI/M2/Projet/Remote-Sensing-Image/starting_kit/sample_data/Areal_train.data\n",
      "[+] Success in  0.82 sec\n",
      "========= Reading /home/keanu/Documents/CoursMPI/M2/Projet/Remote-Sensing-Image/starting_kit/sample_data/Areal_train.solution\n",
      "[+] Success in  0.00 sec\n",
      "========= Reading /home/keanu/Documents/CoursMPI/M2/Projet/Remote-Sensing-Image/starting_kit/sample_data/Areal_valid.data\n",
      "[+] Success in  0.16 sec\n",
      "========= Reading /home/keanu/Documents/CoursMPI/M2/Projet/Remote-Sensing-Image/starting_kit/sample_data/Areal_valid.solution\n",
      "[+] Success in  0.00 sec\n",
      "========= Reading /home/keanu/Documents/CoursMPI/M2/Projet/Remote-Sensing-Image/starting_kit/sample_data/Areal_test.data\n",
      "[+] Success in  0.16 sec\n",
      "========= Reading /home/keanu/Documents/CoursMPI/M2/Projet/Remote-Sensing-Image/starting_kit/sample_data/Areal_test.solution\n",
      "[+] Success in  0.00 sec\n",
      "DataManager : Areal\n",
      "info:\n",
      "\tusage = Sample dataset Areal data\n",
      "\tname = areal\n",
      "\ttask = multiclass.classification\n",
      "\ttarget_type = Categorical\n",
      "\tfeat_type = Numerical\n",
      "\tmetric = accuracy\n",
      "\ttime_budget = 12000\n",
      "\tfeat_num = 49152\n",
      "\ttarget_num = 13\n",
      "\tlabel_num = 13\n",
      "\ttrain_num = 65\n",
      "\tvalid_num = 13\n",
      "\ttest_num = 13\n",
      "\thas_categorical = 0\n",
      "\thas_missing = 0\n",
      "\tis_sparse = 0\n",
      "\tformat = dense\n",
      "data:\n",
      "\tX_train = array(65, 49152)\n",
      "\tY_train = array(65, 1)\n",
      "\tX_valid = array(13, 49152)\n",
      "\tY_valid = array(13, 1)\n",
      "\tX_test = array(13, 49152)\n",
      "\tY_test = array(13, 1)\n",
      "feat_type:\tarray(0,)\n",
      "feat_idx:\tarray(49152,)\n",
      "\n",
      "[+] Size of uploaded data  56.00 bytes\n",
      "[+] Cumulated time budget (all tasks so far)  12000.00 sec\n",
      "[+] Time budget for this task 12000.00 sec\n",
      "[+] Remaining time after reading data 11998.82 sec\n",
      "======== Creating model ==========\n",
      "**********************************************************\n",
      "****** Attempting to reload model to avoid training ******\n",
      "**********************************************************\n",
      "Model reloaded from: /home/keanu/Documents/CoursMPI/M2/Projet/Remote-Sensing-Image/starting_kit/sample_code_submission/Areal_model.pickle\n",
      "[+] Model reloaded, no need to train!\n",
      "[+] Prediction success, time spent so far  1.31 sec\n",
      "======== Saving results to: /home/keanu/Documents/CoursMPI/M2/Projet/Remote-Sensing-Image/starting_kit/sample_result_submission\n",
      "[+] Results saved, time spent so far  1.31 sec\n",
      "[+] End cycle, time left 11998.69 sec\n",
      "[+] Done\n",
      "[+] Overall time spent  2.05 sec ::  Overall time budget 12000.00 sec\n"
     ]
    }
   ],
   "source": [
    "!python3 $problem_dir/ingestion.py $data_dir $result_dir $problem_dir $model_dir"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Test scoring program"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "======= Set 1 (Areal_test): accuracy(set1_score)=0.230769230769 =======\r\n",
      "======= Set 2 (Areal_train): accuracy(set2_score)=0.400000000000 =======\r\n",
      "======= Set 3 (Areal_valid): accuracy(set3_score)=0.307692307692 =======\r\n"
     ]
    }
   ],
   "source": [
    "scoring_output_dir = 'scoring_output'\n",
    "!python3 $score_dir/score.py $data_dir $result_dir $scoring_output_dir"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prepare the submission"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Submit one of these files:\n",
      "./sample_code_submission_19-01-11-18-43.zip\n",
      "./sample_result_submission_19-01-11-18-43.zip\n"
     ]
    }
   ],
   "source": [
    "import datetime \n",
    "from data_io import zipdir\n",
    "the_date = datetime.datetime.now().strftime(\"%y-%m-%d-%H-%M\")\n",
    "sample_code_submission = './sample_code_submission_' + the_date + '.zip'\n",
    "sample_result_submission = './sample_result_submission_' + the_date + '.zip'\n",
    "zipdir(sample_code_submission, model_dir)\n",
    "zipdir(sample_result_submission, result_dir)\n",
    "print(\"Submit one of these files:\\n\" + sample_code_submission + \"\\n\" + sample_result_submission)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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